External Validation of Models for Predicting Pneumonia after Cardiac Surgery
作者： Marisa da Silva Santos , Bernardo Rangel Tura , Alexandre Rouge , José Ueleres Braga
DOI: 10.1089/SUR.2010.014
关键词: Predictive modelling 、 Cardiothoracic surgery 、 Cart 、 Cardiac surgery 、 Emergency medicine 、 Pneumonia 、 Risk assessment 、 Logistic regression 、 Medicine 、 Intensive care medicine 、 Derivation
摘要: Abstract Background: Approximately 20% of patients become infected after cardiac surgery. Pneumonia is one the most serious infections, increasing chance death 14-fold. The higher frequency pneumonia surgery may be explained by surgical conditions. Focusing on high-risk groups make several strategies more effective, and external validation an essential phase building prediction models to identify such groups. Purpose: To compare performance two previously validated for (classification regression tree [CART] a logistic model [LRM]) set. Methods: A series 527 adult at small private hospital were analyzed prospectively prognostic factors pneumonia. occurred in 7.6% this derivation probability onset was estimated means CART LRM using cut-off point that maximized both se...
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